Understanding Polarization Correlation of Entangled Vector Meson Pairs

We propose an experimental test of local hidden variable theories against quantum mechanics by measuring the polarization correlation of entangled vector meson pairs. In our study, the form of the polarization correlation probability is reproduced in a natural way by interpreting the two-body decay of the meson as a measurement of its polarization vector within the framework of quantum mechanics. This provides more detailed information on the quantum entanglement, thus a new Monte Carlo method to simulate the quantum correlation is introduced. We discuss the feasibility of carrying out such a test at experiments in operation currently and expect that the measured correlated distribution may provide us with deeper insight into the fundamental question about locality and reality.Comment: 7 pages, 3 figures. v3: The version published in PR

Unifizierte Service-Komposition für ConDec

In der Arbeit wird die Implementierung einer Transformation von der deklarativen Sprache ConDec zur Kompositionsgrammatiken diskutiert. In der Forschung besteht die Hoffnung, dass der assembler-ähnliche Charakter von Kompositionsgrammatiken die Grundlage für die unifizierte Modellierung bilden kann. Zuerst werden Web Services und ihre Kompositionen in der Arbeit vorgestellt. Web Services sind die Abstraktionen für verschiedene Plattformen und Sprachen, so dass die Aufrufe von Web Services gleich sind. Ihre Kompositionen beschreiben die Art und Weise wie Web Services miteinander verknüpft sind. Dann wird der Begriff de-klarative Sprache beschrieben. Die Vorgehensweise von imperativen Sprachen ist "say how to do something". Zum Unterschied von imperativen Sprachen ist die Vorgehensweise deklarativer Sprachen "say what is required and let the system determine how to achieve it". Durch den Vergleich ist es klar, dass die deklarativen Sprachen die beiden Anforderungen zwischen Unterstützung und Flexibilität von Systemen gut ausgleichen können. Danach werden Con-Dec und die Software Declare vorgestellt. ConDec ist eine deklarative Sprache und die Software Declare unterstützt ConDec. Dann wird die Implementierung der Transformation aus-führlich beschrieben. Durch das Klassendiagramm werden die Funktionen der Klassen vom Transformationspragramm vorgestellt. Das Aktivitätsdiagramm beschreibt den Ablauf vom Transformationspragramm. Darüber hinaus wird eine detaillierte Diskussion über die Heraus-forderungen der Transformation geführt. Die Diskussion ist über einige Templates, die in der Arbeit nicht vorkommen. Zum Schluss werden zwei Testfälle geprüft, die die eigenen Beispiele in declare-2.2.0 sind

Uncertainty Minimization for Personalized Federated Semi-Supervised Learning

Since federated learning (FL) has been introduced as a decentralized learning technique with privacy preservation, statistical heterogeneity of distributed data stays the main obstacle to achieve robust performance and stable convergence in FL applications. Model personalization methods have been studied to overcome this problem. However, existing approaches are mainly under the prerequisite of fully labeled data, which is unrealistic in practice due to the requirement of expertise. The primary issue caused by partial-labeled condition is that, clients with deficient labeled data can suffer from unfair performance gain because they lack adequate insights of local distribution to customize the global model. To tackle this problem, 1) we propose a novel personalized semi-supervised learning paradigm which allows partial-labeled or unlabeled clients to seek labeling assistance from data-related clients (helper agents), thus to enhance their perception of local data; 2) based on this paradigm, we design an uncertainty-based data-relation metric to ensure that selected helpers can provide trustworthy pseudo labels instead of misleading the local training; 3) to mitigate the network overload introduced by helper searching, we further develop a helper selection protocol to achieve efficient communication with negligible performance sacrifice. Experiments show that our proposed method can obtain superior performance and more stable convergence than other related works with partial labeled data, especially in highly heterogeneous setting.Comment: 11 page

Association between platelet count and the risk and progression of hand, foot, and mouth disease among children

OBJECTIVE: We aimed to evaluate the association between platelet (PLT) count and the risk and progression of hand, foot, and mouth disease (HFMD). METHODS: In total, 122 HFMD patients and 40 healthy controls were enrolled in the study. The differences between variables among the different subgroups were compared. Logistic regression analyses were performed to assess the relationship between various parameters and HFMD risk/progression. Sensitivity analysis was conducted by detecting the trend of the association between PLT count quartiles and HFMD risk/progression. A generalized additive model was used to identify the nonlinear relationship between PLT count and HFMD risk/ progression. The relationship between gender and PLT count as well as the risk/progression of HFMD was detected using a stratified logistic regression model. RESULTS: Significant differences were observed in terms of age, male/female ratio, white blood cell (WBC) count, and PLT count between patients with stage I-II, III-IV HFMD and healthy controls. Moreover, the alanine aminotransferase and magnesium levels between patients with stage I-II and III-IV HFMD significantly differed. Moreover, a significant difference was noted in the male/female ratio among the different PLT groups. The group with a low PLT count had a lower risk of HFMD progression than the group with a high PLT count (Q4) (p=0.039). Lower age, male gender, and WBC count were found to be associated with HFMD risk. Meanwhile, PLT count was correlated to HFMD progression. The sensitivity analysis yielded a similar result using the minimally adjusted model (p for trend=0.037), and minimal changes were observed using the crude and fully adjusted model (p for trend=0.054; 0.090). A significant nonlinear relationship was observed between PLT count and HFMD progression after adjusting for age, gender, and WBC (p=0.039). CONCLUSIONS: PLT was independently associated with HFMD progression in a nonlinear manner

Probing darK Matter Using free leptONs: PKMUON

We propose a new method to detect sub-GeV dark matter, through their scatterings from free leptons and the resulting kinematic shifts. Specially, such an experiment can detect dark matter interacting solely with muons. The experiment proposed here is to directly probe muon-philic dark matter, in a model-independent way. Its complementarity with the muon on target proposal, is similar to, e.g. XENON/PandaX and ATLAS/CMS on dark matter searches. Moreover, our proposal can work better for relatively heavy dark matter such as in the sub-GeV region. We start with a small device of a size around 0.1 to 1 meter, using atmospheric muons to set up a prototype. Within only one year of operation, the sensitivity on cross section of dark matter scattering with muons can already reach $\sigma_D\sim 10^{-19 (-20,\,-18)}\rm{cm}^{2}$ for a dark mater $\rm{M_D}=100\, (10,\,1000)$ MeV. We can then interface the device with a high intensity muon beam of $10^{12}$/bunch. Within one year, the sensitivity can reach $\sigma_D\sim 10^{-27 (-28,\,-26)}\rm{cm}^{2}$ for $\rm{M_D}=100\, (10,\,1000)$ MeV.Comment: 5 pages, 3 figures, muons enlighten darknes

Using SVD on Clusters to Improve Precision of Interdocument Similarity Measure

Recently, LSI (Latent Semantic Indexing) based on SVD (Singular Value Decomposition) is proposed to overcome the problems of polysemy and homonym in traditional lexical matching. However, it is usually criticized as with low discriminative power for representing documents although it has been validated as with good representative quality. In this paper, SVD on clusters is proposed to improve the discriminative power of LSI. The contribution of this paper is three manifolds. Firstly, we make a survey of existing linear algebra methods for LSI, including both SVD based methods and non-SVD based methods. Secondly, we propose SVD on clusters for LSI and theoretically explain that dimension expansion of document vectors and dimension projection using SVD are the two manipulations involved in SVD on clusters. Moreover, we develop updating processes to fold in new documents and terms in a decomposed matrix by SVD on clusters. Thirdly, two corpora, a Chinese corpus and an English corpus, are used to evaluate the performances of the proposed methods. Experiments demonstrate that, to some extent, SVD on clusters can improve the precision of interdocument similarity measure in comparison with other SVD based LSI methods